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Online Detection of Repeated Structures in Point Clouds of Urban Scenes for Compression and Registration

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Abstract

Laser range scans of urban areas have a distinctive geometry dominated by facade and ground planes and repetitive regular fenestration. Detection of these ubiquitous features provides profound insights into the scene. We present a novel method for detecting major planes and repetitive architectural features. Armed with this knowledge we illustrate its application in compression and registration of range scans. What is more our algorithm operates online, processing the scan as it is retrieved by the scanner. This realtime approach opens up new possibilities in range data segmentation, compression and registration.

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Notes

  1. We will use the terms column and scanline interchangeably.

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Authors and Affiliations

  1. Hunter College & Graduate Center of CUNY, CUNY, New York City, NY, USA

    Sam Friedman & Ioannis Stamos

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  1. Sam Friedman
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  2. Ioannis Stamos
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Correspondence to Ioannis Stamos.

Additional information

This work has been supported in part by the following NSF grants: IIS-0915971, CCF-0916452 and MRI CNS-0821384. We would like to thank Tom Flynn for his labeling and registration software. We are also thankful to the anonymous reviewers for their helpful comments.

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Friedman, S., Stamos, I. Online Detection of Repeated Structures in Point Clouds of Urban Scenes for Compression and Registration. Int J Comput Vis 102, 112–128 (2013). https://doi.org/10.1007/s11263-012-0575-y

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  • DOI: https://doi.org/10.1007/s11263-012-0575-y

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